I built a tool that stress-tests every locale before a screen ships
Most teams write in English, ship the design, then send strings out and hope the result still fits. I designed and built an AI-powered stress-tester that renders eight locales live on the real screen, so I can catch breakage in design, not in QA.
Localization was the last step. English copy went out as a string list and came back days later. I met the breakage in QA, not in design.
I built an AI tool that renders eight locales live on the real screen, so layout strain shows up the moment a word lands.
The tool now handles 90% of manual localization review, freeing two content designers for higher-impact work.
Why was localization always cleanup, never design?
The old loop treated localization as the final chore. I wrote English copy, exported a string list, sent it out, and pasted the result back. By the time I saw a translation in context, the design was three sprints old.
So breakage surfaced in QA. A German compound word overflowed a button. Cyrillic pushed a label onto two lines. An Arabic screen needed mirroring no one had checked. None of it was a translation error. It was a design problem that nobody could see until it was expensive to fix.
Move every locale into the design, not after it.
I stopped translating finished screens. Instead I built a tool that renders all eight locales live on the real component, so I transcreate the screen rather than translate a spreadsheet. Layout pressure becomes a design decision again.
A string list, sent out, returned days later.
Strings exported to a CMS, emailed to vendors, pasted back. I saw the breakage in QA. Tone, density and direction got patched, never designed.
One screen, eight locales, live.
I paste a screen and fan it out across LTR and RTL locales. Overflow and fit flags appear the moment a word lands, while the design is still mine to change.
Stress-test preview: eight locales, one screen.
Paste a screen, fan it out, watch the layout react. The locales that strain flag themselves before anything reaches QA.
Try it: tap Highlight overflow above to flag the locales the design system cannot hold.
The AI proposes. I decide. Every change is traceable.
Every field and locale sits in one grid. The AI handles the literal pass; I keep the judgment. Tap any green cell to see the original suggestion and why I changed it.
| Field | EN | ES | PT | RU | ZH | AR | TR | DE |
|---|---|---|---|---|---|---|---|---|
| Cards | ||||||||
| Card 1 label | Recurring buy | Compra recurrente | Compra recorrente | Регулярная покупка | 定期购买 | شراء متكرر | Yinelenen alim | Dauerauftrag |
| Card 2 label | Trigger orders | Orden activada | Ordem gatilho | Триггер-ордер | 触发订单 | أمر مشروط | Tetik emri | Trigger-Order |
| Card 3 label | Trading bots | Bots de trading | Bots de trading | Торговые боты | 交易机器人 | روبوتات التداول | Ticaret botlari | Trading-Bots |
| Pending | ||||||||
| Item 1 title | Deposit USD | Depositar USD | Depositar USD | Пополнение USD | 存入美元 | إيداع دولار | USD Yatir | USD einzahlen |
| Item 2 title | Withdraw ETH | Retirar ETH | Retirar ETH | Вывод ETH | 提现ETH | سحب ETH | ETH Cek | ETH abheben |
| Buttons | ||||||||
| Transfer button | Transfer | Transferir | Transferir | Перевод | 转账 | تحويل | Transfer | Uebertragen |
| Buy & sell button | Buy and sell | Comprar y vender | Comprar e vender | Купить и продать | 买入和卖出 | شراء وبيع | Al ve sat | Kaufen & Verkaufenedited AI › Kaufen und verkaufen Sie The model returned an imperative sentence. A button needs a label, so I tightened it to a noun phrase the component can hold. |
| Nav | ||||||||
| Nav: Home | Home | Inicioedited AI › Pagina de inicio Literal and correct, but too long for a nav item. "Inicio" matches the rest of the bar and keeps the tab tappable. | Inicio | Главная | 首页 | الرئيسية | Ana Sayfa | Startseite |
| Nav: Portfolio | Portfolio | Portafolio | Portfolio | Портфель | 投资组合 | المحفظة | Portfoy | Portfolio |
Try it: tap any cell marked edited to see the AI's first pass and my reasoning.
"Buy and sell" does not translate. It reshapes.
Watch one button change weight, width and direction across eight locales. This is the reason localization cannot live in a spreadsheet.
I designed the prompts, so the AI carries the manual load.
The tool is only as good as what it is told. I treated the prompt as a content brief: tone, audience and product context, written once and reused on every run.
Map the screen
Every label, button and status is pulled from the source UI into a structured field grid, so nothing gets lost between design and copy.
Brief the model with intent
I give the AI tone, audience and product context up front. It transcreates for meaning and fit, not a literal word-for-word swap.
Render the pressure
Each locale pours back into the live component. Overflow and fit flags appear instantly across LTR and RTL.
Review only the exceptions
The AI clears the routine 90%. I spend my time on the flagged cells, the cultural judgment calls and the layout decisions that need a human.
The tool now does the review I used to do by hand.
0%
of manual localization review is now automated, freeing two content designers to focus on higher-impact work while the tool handles the routine pass.
Localization is a design problem./ The principle behind the build
What I learned, and what I would pressure-test next.
Treating the prompt as a content brief was the unlock. The quality of the output tracked the quality of the context I gave it, not the model.
Automating 90% only works because the last 10% is visible. The override trail keeps every AI suggestion accountable to a content designer.
Wiring the tool into the design system tokens directly, so overflow flags reflect the exact component a screen will ship in.